The City of Amsterdam is responsible for the maintenance of 600 km of historic quay walls, most of which are over 100 years old while others are 300 years old and are experiencing stability and degradation problems. A lack of knowledge about the as-built information and the current conditions of the retaining structures and their foundation systems exists, and very limited guidelines for the assessment of quay walls are available. Predicting the time when the quay walls are no longer safe is a key challenge in their end-of-life assessment. For this purpose, monitoring of the quay walls via conventional techniques (e.g., in situ surveys, topographic levelling and tachymetry) combined with satellite Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) data provides updated information on the displacements affecting the retaining structures and/or their foundations. This paper develops a multiscale methodology, consisting of three phases, that allow (1) the prioritization of the most exposed retaining structures (quay walls) at the municipal scale, (2) the retrieval of empirical relationships between different damage/movement indicators and quantitative displacement descriptors obtained via in situ surveys and terrestrial monitoring data, and (3) the identification of the most probable collapse mechanism by jointly analyzing the wall crack patterns and monitoring data. The results show that this approach could play a fundamental role to set up sustainable risk mitigation strategies at the municipal scale.

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This study presents a novel framework in which numerical modelling contributes to the performance of district-scale, subsidence-induced damage assessment in cities where ground settlements affect entire quarters. Therein, the implementation of expeditious procedures offers geotechnical engineers the possibility of contributing beyond the typical site scale. For this purpose, several “typified” hydro-geomechanical-loading (HGL) models, which represent (simplified) scenarios of masonry buildings undergoing settlements, were set up to account for different predisposing or triggering factors (i.e., soil heterogeneity, loading conditions, and groundwater variations) of settlement occurrence in built-up areas. These models exploit multi-source, wide-area input datasets encompassing the hydro-mechanical properties of geomaterials, in situ investigations and measurements (e.g., groundwater levels in wells), and innovative remote sensing data (i.e., DInSAR techniques). With reference to a district in Rotterdam City (the Netherlands), which was built on “soft soils”, the numerical simulations of different scenarios (i) provide an overview of the comparative role of predisposing or triggering factors on settlement occurrence and (ii) allow assessments of the expected induced damage to masonry buildings over 30 years with the exploitation of fragility curves. Considering the widespread diffusion of such geohazards, the proposed approach could help prioritise (rather expensive) maintenance work to the built heritage within sustainable strategies for subsidence risk mitigation.

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This paper presents an integrated analysis based on the use of multi-source wide-area datasets consisting of hydro-mechanical properties of geomaterials, in-situ investigations/measurements (e.g. groundwater levels in wells) and innovative space-borne data (i.e. DInSAR techniques) to support numerical analyses aimed at assessing and predicting the settlements affecting built-up areas in variable soil conditions. To this aim, an expeditious procedure was developed and tested with reference to a district in Rotterdam City (The Netherlands) affected by subsidence phenomena due to the presence of heterogeneous settling strata mainly composed by peat and organic soils. The results obtained allowed investigating the role of predisposing factors of the settlement occurrence and assessing the induced damage on buildings. Considering the widespread diffusion of such geohazards, the followed procedure could help the in-charge authorities to carry out activities at urban scale aimed at identifying the areas most affected by subsidence risk and to select the most suitable and sustainable mitigation strategies.@en

The paper presents a probabilistic analysis aimed at identifying the most appropriate subsidence related intensity (SRI) parameter (e.g., differential settlement, relative rotation, deflection ratio) that can be used to forecast the severity level of building damage at municipal scale through the generation of empirical fragility and vulnerability curves. The analysis refers to a rich sample of more than seven hundred monitored (by remote sensing techniques) and surveyed masonry buildings – mainly resting with their (shallow or piled) foundations on highly compressible fine-grained “soft soils” – affected by settlements in four urban areas in The Netherlands. The achieved outcomes, once further calibrated and validated, could allow for an improvement of existing geotechnical damage criteria for buildings as well as help local authorities in charge of the management/protection of subsiding urban areas to plan adequate foundation repairing/replacing measures before damage reaches intolerable severity levels.

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The analysis and prediction of damage to buildings resting on highly compressible fine-grained “soft soils” containing (organic) clay and peat are key issues to be addressed for a proper management of subsidence-affected urban areas. Among the probabilistic approaches suggested in literature, those oriented to the generation of empirical fragility curves are particularly promising provided that a comprehensive dataset for both the subsidence-related intensity (SRI) parameters and the corresponding damage severity to buildings is available. Following this line of thought, in the present paper, a rich sample of more than seven hundred monitored (by remote sensing) and surveyed masonry buildings – mainly resting with their (shallow or piled) foundations on soft soils – is analysed in four urban areas of The Netherlands. Probabilistic functions in the form of fragility curves for building damage are retrieved for three different SRI parameters (i.e., differential settlement, rotation and deflection ratio) derived from the processing of Synthetic Aperture Radar (SAR) images by way of a differential interferometric (DInSAR) technique in combination with the severity levels of the damage recorded from the visual inspection of over 700 masonry buildings. As a novelty with respect to earlier similar studies, the work points out the methodological steps to be followed in order to identify the most appropriate SRI parameter among the selected ones. Thus, the objective of the paper is to improve the existing geotechnical forecasting tools for subsidence-affected urban areas, in order to target areas that require more detailed investigations/analyses and/or to select/prioritize foundation repairing/replacing measures.@en